Your Street, Your Say: Better streets for Darebin
The goal of this project is to recommend interventions and projects to turn streets into better public spaces by building on aspirations of the local community.
The relationship between vehicle telemetry and sustainability
The objective of this PhD project is to analyse the relationship between telemetry and its impact on commercially sustainable transportation solutions/networks.
VIDEO: Innovative community transport webinar
Watch the video recording of our webinar discussing the final report of our ‘Innovative local transport: Community transport of the future’ project.
Community transport: Defining the problems, fixing the future
Download the final report from iMOVE’s ‘Innovative local transport: Community transport of the future’ project.
Defining transport disadvantage in Perth
Literature review/stakeholder interviews to guide the estimation of the extent, spatial distribution, & nature of transport disadvantage in the Greater Perth region.
WEBINAR: Community transport of the future
Register for our webinar ‘Delivering community transport that meets the diverse needs of our growing population’, and improve its service and accessibility.
Developing an urban freight planning course: A scoping study
A scoping study to identify opportunities to improve urban freight planning tertiary education in Australia, improving education outcomes for freight logistics.
Will Working from Home continue? And how?
Our ‘Encouraging continuation of work from home post-pandemic’ project has been completed, and the final report is available here.
Emergency facilities location and transportation routing
This PhD project will develop traffic management strategies and infrastructure allocation algorithms needed to improve emergency vehicle logistics.
A model for estimating delays at traffic signals
This project will create a model for estimating delays at Perth’s traffic signals, which would inform project decisions and operational strategies.
Real-time crash risk estimation using machine learning
Using state-of-the-art machine learning algorithms, this study will use a novel modelling approach to accurately predict traffic crashes in real-time.
Building trust and collaboration among MaaS stakeholders
This PhD project will, at its conclusion, demonstrate how the roles and responsibilities of different stakeholders impact building a collaborative MaaS environment.
Implementation of sustainable transport policies
This PhD project explores cycle lane implementation from both a policymaker’s and user’s perspective, and flexible transport solutions for rural users.
Scenario developments for forecasting urban freight shifts
This project will develop a framework/tool for forecasting future scenarios of urban freight in informing planning and regulation (transport and land use).
Bus performance assessment using GTFS data
This PhD project will analyse archived GTFS data to identify significant inefficient road designs and exemplary designs for optimising performance
Optimising multimodal transport networks: Sharing road space
This research will focus on enhanced depiction of pedestrian and active mode interactions with vehicular traffic across a variety of road infrastructure scenarios.